• Energy Research

Recent years have seen a rise in the frequency and severity of extreme rainstorm events, which have caused widespread damage and death in numerous cities. The manufacture and use of storm drainage materials result in numerous environmental concerns in the construction industry. Green materials for storm drainage networks are environmentally friendly compared to their traditional counterparts. Identifying and assessing sustainability criteria for green materials for storm drain networks has been challenging. This study aims to determine the critical criteria for selecting green materials for storm drainage networks using a stationary analysis approach. To this end, a questionnaire survey was administered to Egyptian storm engineers to assess their importance based on a selection criteria 29 green materials. From the results obtained, “Operation and maintenance cost” and “Use of local material” were seen to be the “stationary materials”. The obtained findings in this research pave the way for the Egyptian storm industry towards becoming environmentally friendly, which will in turn improve the functioning mechanism of sewer networks.

Abstract The construction industry has always been infamous due to its staggering numbers of Occupational Health and Safety (OHS)-related injuries, resulting from overlooking all the crucial aspects endangering the involved workers’ lives. Considering this, there has been dearth of a study including all the essential Risk Parameters (RPs) for comprehensively assessing the OHS in the construction industry. Theretofore, a Holistic Occupational Health and Safety Risk Assessment Model (HOHSRAM) is developed in the current study to assess the safety and health of the Construction Workers (CWs’). The developed model is based on the integration of logarithmic fuzzy ANP, interval-valued Pythagorean fuzzy TOPSIS, and grey relational analysis. Based on the application of the developed HOHSRAM to a case of sustainable construction project, the following contributions have been noted; (1) calculating weights related to the safety decision makers having different backgrounds involved in the study using logarithmic-fuzzy-based constrained optimization algorithm, (2) involving the individual biases of the decision makers in the assessment stage, (3) determining all the essential RPs to comprehensively assess the OHS within the construction projects in a systematic way, (4) obtaining the final rankings of the identified safety risks under an interval-valued-Pythagorean fuzzy environment coupled with grey relational analysis. Additionally, it is discerned that the proposed model in this research outperforms the existing assessment methods used in the construction industry, through conducting a comprehensive comparative analysis. The developed HOHSRAM is verified to be beneficial for safety professionals by providing them with an inclusive ranking system, improving the well-being of the involved CWs.

Abstract Green roofs (GRs) have several private, environmental, and social benefits, though financial issues have been considered a major barrier to its widespread use. The lack of knowledge and information regarding the value and applicability of each such benefit has resulted in limited adoption of GRs in Malaysia. Hence, the aim of this research is to analyse the financial feasibility of GR installation, considering social and private perspectives (where the applicability of benefits varies across various scenarios). To do that, the applicable short- and long-term costs and benefits of GRs were identified through reviewing the literature. Then, the variables’ values were investigated and calculated using Monte Carlo simulation. GRs’ net present value (NPV) and discounted payback period (DPBP) were analysed in different private scenarios to derive its financial feasibility out in Kuala Lumpur. Additionally, projected social benefits were analysed to indicate the government’s financial benefit from GR adoption. The results showed that NPV for the private sector could be up to $1072.44 m2 and $735.11 m2, while it is most likely around $390.78 m2 and $258 m2 for intensive GR (IGR) and extensive GR (EGR), respectively. Most probably, the DPBP would be between one and nine years and one and six years for IGR and EGR, respectively. Additionally, considering the social benefits of GR, IGR has the potential to offer up to $314 m2; the amount is much lower for EGR at $55 m2. Moreover, it was found that energy saving is the most influential variable affecting NPV in private and social perspectives. Finally, it was concluded that GR installation could be financially feasible if all private benefits are applicable. Since GR has social financial benefits, the initial costs could be partially covered by the government as an incentive for GR installers.

Abstract This paper presents a comprehensive review of the significant studies exploited Artificial Neural Networks (ANNs) in BEA (Building Energy Analysis). To achieve a full coverage of the relevant studies to the scope of the research, a three-decade time span of the publishing date of the existing studies was taken into account. The review focuses on the studies utilized ANN to analyze the energy-related issues associated with buildings in major areas, including modeling of water heating and cooling systems, heating and cooling loads prediction, modeling heating ventilation air conditioning systems, indoor air temperature prediction, and building energy consumption prediction. Moreover, the findings of the abundant reviewed studies along with the potential future research to be carried out are discussed elaborately. Regarding the comprehensive review conducted, it is found out that the majority of studies focused on building energy consumption and indoor air temperature prediction. Additionally, it is observed that there has been a growing interest in the application of newly-developed ANNs to BEA areas, such as general regression neural network and recurrent neural network, due to their abilities in improving the modeling and prediction of buildings energy analysis. It is believed that this thorough review paper is useful for the researchers and scientific engineers working on the application of AI-based techniques to the building-energy-related areas to find out the relevant references and current state of the field.

Green roofs are known as one of the environmentally-friendly applications and also as a sustainable approach in developing countries. Although many researchers have proven the environmental benefits of installing green roofs all around the world, they have not been used widely in many countries due to the lack of knowledge about cost-benefit issues. This paper places an emphasis on all the private factors affecting cost-benefit analysis. Installation, operation and maintenance costs are compared with the benefits such as energy saving, the increase in property value, and the acoustic effect in order to determine two indicators namely “net present value” and “pay-back period,” using the Monte Carlo simulation. Two scenarios are considered in the analyses: using the property, and selling the property after construction. Moreover, correlation and regression sensitivity analyses are also conducted. The capital of Malaysia, Kuala Lumpur, is selected for the case study due to the lack of cost-benefit analysis in developing countries. The results show that there is low probability of loss in the installation of both types of green roofs during their lifespans. Moreover, net present value for intensive green roofs is found to be higher than extensive ones, whereas the payback period for installing extensive green roofs is lower than intensive green roofs. It is concluded that the probability of loss for the owner is higher than that of benefit in the scenario of selling the property after construction resulting from the installation of both types of green roofs.

This study aims to model the performance of sewage networks under diverse blockage situations in terms of overflow occurrence using internet-of-things-based technologies in Hong Kong. To this end, a multi-stage methodological approach is employed, starting from collecting required data using smart sensors, utilizing novel data mining techniques, and using a case study simulation. From the results obtained, the following conclusions are drawn: (1) several sites under investigation are imbued with partial blockages, (2) the overall performance of the sewer network has a nonlinear relationship with the blockages in terms of the remaining time to overflow, (3) in cases of complete blockages, the sewer only takes few minutes to reach the manhole cover level that causes the system to experience overflow, and (4) cleaning work significantly improve the performance of the sewage network by 86%. The outcomes of this study provide a solid foundation for the concerned environmental engineers and decision-makers towards reducing the magnitude of sewer overflow and improving different aspects of our environment.

Abstract The benefits (B), opportunities (O), costs (C), and risks (R) of green roof (GR) installation have been identified by several studies. However, the inner-dependencies among them, potentially significant in the decision-making process for proper adoption of GRs, have not yet been investigated. In view of this gap, this study investigates the inner-dependencies between the BOCRs of GR installation according to Malaysian experts. BOCRs were collated through a review of the literature and categorized into 11 groups. The enhanced fuzzy Delphi method (EFDM) and fuzzy decision-making trial and evaluation laboratory (FDEMATEL) approaches were utilized to investigate the inner-dependencies. The EFDM results revealed that 28 BOCRs were perceived as significant, while the investigation of inner-dependencies showed that stormwater management, contribution to mitigation of urban heat islands, additional structural support, and irregular maintenance were the most influential B, O, C, and R, respectively. Notably, no significant relationships were found among environmental and economic opportunities. FDEMATEL results showed that, to take full advantage of GR installation, the primary focus should be on the most influential (rather than important) Bs and Os. The findings of this research provide stakeholders with insights into the adoption of GR installation, bringing not only environmental benefits but financial upsides.

Although many studies have focused on digital transformation and sustainability within the realm of project management, there has been a lack of research that comprehensively reviews the current state of the art of the aforementioned subject using a holistic approach. This oversight hampers the amalgamation of DT and sustainability in project management, waning the steps to be taken for the realisation of a smart and sustainable built environment. To fill the identified knowledge gap, this study presents a science mapping approach to meticulously examine the literature published on DT and sustainability within the realm of project management. In doing so, a bibliometric review together with a comprehensive Scientometric mapping analysis was carried out on the literature published from 2011 to 2022. The findings obtained in this study provide insightful accounts for both project managers and academics. Project managers are not only enlightened on revamping their business models but are also given insights into utilising digital strategies for bringing the maximum level of sustainability into their projects. Meanwhile, researchers are given insight into the emerging trends, timelines, and emerging streams that will be explored in future endeavours.